Stochastic Gradient Descent

 Kaggle Learn Courses

Introduction In the first two lessons, we learned how to build fully-connected networks out of stacks of dense layers. When first created, all of the network's weights are set randomly -- the network...

Stochastic Gradient Descent

 Dive intro Deep Learning Book

In earlier chapters we kept using stochastic gradient descent in our training procedure, however, without explaining why it works. To shed some light on it, we just described the basic principles of g...

1.5. Stochastic Gradient Descent

 Scikit-learn User Guide

Stochastic Gradient Descent (SGD) is a simple yet very efficient approach to fitting linear classifiers and regressors under convex loss functions such as (linear) Support Vector Machines and Logis......

Stochastic Gradient Descent (SGD): Simplified, With 5 Use Cases

 Level Up Coding

It does not have to be so difficult: opportunities and challenges, the simplest guide to SGD. Continue reading on Level Up Coding

Stochastic Gradient Descent — Clearly Explained !!

 Towards Data Science

Stochastic gradient descent is a very popular and common algorithm used in various Machine Learning algorithms, most importantly forms the basis of Neural Networks. In this article, I have tried my…

Stochastic Gradient Descent: Explanation and Complete Implementation from Scratch

 Towards Data Science

Stochastic gradient descent is a widely used approach in machine learning and deep learning. This article explains stochastic gradient descent using a single perceptron, using the famous iris…

Stochastic Gradient Descent: Math and Python Code

 Towards Data Science

Deep Dive on Stochastic Gradient Descent. Algorithm, assumptions, benefits, formula, and practical implementation Image by DALL-E-2 Introduction The image above is not just an appealing visual that d...

Stochastic Gradient Descent

 Analytics Vidhya

Ever wondered of a problem which involves huge data and you have to iterate that one by one and conclude to a conclusion. It will be really a very hectic process & nearly impossible. To solve the…

Stochastic Gradient Descent (SGD)

 Analytics Vidhya

Gradient Descent, a first order optimization used to learn the weights of classifier. However, this implementation of gradient descent will be computationally slow to reach the global minima. If you…

Implementation of Stochastic Gradient Descent

 Analytics Vidhya

The purpose of writing this post is to understand the maths behind gradient descent. Most of us are using gradient descent in machine learning, but we need to understand the maths behind it. As a…

Using Stochastic Gradient Descent to Train Linear Classifiers

 Towards Data Science

A guide to using Stochastic Gradient Descent to efficiently train linear classifiers when the number of training examples or features is large

Stochastic Gradient Descent for machine learning clearly explained

 Towards Data Science

As you may know, supervised machine learning consists in finding a function, called a decision function, that best models the relation between input/output pairs of data. In order to find this…

Stochastic-, Batch-, and Mini-Batch Gradient Descent Demystified

 Towards Data Science

This is a detailed guide that should answer the questions of why and when we need Stochastic-, Batch-, and Mini-Batch Gradient Descent when implementing Deep Neural Networks.

Gradient Descent

 Analytics Vidhya

Step-by-Step Tutorial on Linear Regression with Stochastic Gradient Descent

 Towards Data Science

This article should provide you a good start for us to dive deep into deep learning. Let me walk you through the step-by-step calculations for a linear regression task using stochastic gradient…

Stochastic Gradient Descent in Deep Learning

 Analytics Vidhya

Neural Network often consist of millions of weights which we need to find the right value for. Optimizing this networks with available data needs careful consideration of the optimizer to be chosen…

A Newbie's Guide to Stochastic Gradient Descent With Restarts

 Towards Data Science

Simply finding a learning rate to undergo gradient descent will help minimize the loss of a neural network. However, there are additional methods that can make this process smoother, faster, and more…...

Learning Parameters, Part 3: Stochastic & Mini-Batch Gradient Descent

 Towards Data Science

In part 2, we looked at two useful variants of gradient descent — Momentum-Based and Nesterov Accelerated Gradient Descent. In this post, we are going to look at stochastic versions of gradient…

Stochastic Gradient Descent with momentum

 Towards Data Science

This is part 2 of my series on optimization algorithms used for training neural networks and machine learning models. Part 1 was about Stochastic gradient descent. In this post I presume basic…

The ins and outs of Gradient Descent

 Towards Data Science

Gradient descent is an optimization algorithm used to minimize some cost function by iteratively moving in the direction of steepest descent. That is, moving in the direction which has the most…

Gradient Descent

 Dive intro Deep Learning Book

In this section we are going to introduce the basic concepts underlying gradient descent . Although it is rarely used directly in deep learning, an understanding of gradient descent is key to understa...

A Visual Guide to Stochastic, Mini-batch, and Batch Gradient Descent

 Daily Dose of Data Science

Gradient descent is a widely used optimization algorithm for training machine learning models. Stochastic, mini-batch, and batch gradient descent are three different variations of gradient descent, an...

Why Stochastic Gradient Descent Works?

 Towards Data Science

Optimizing a cost function is one of the most important concepts in Machine Learning. Gradient Descent is the most common optimization algorithm and the foundation of how we train an ML model. But it…...

Linear Regression Tutorial Using Gradient Descent for Machine Learning

 Machine Learning Mastery

Last Updated on February 10, 2021 Stochastic Gradient Descent is an important and widely used algorithm in machine learning. In this post you will discover how to use Stochastic Gradient Descent to le...